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<strong>Neural network modeling of forces in drilling of glass/epoxy composites filled with agro-based waste materials</strong>

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Title Statement <strong>Neural network modeling of forces in drilling of glass/epoxy composites filled with agro-based waste materials</strong>
 
Added Entry - Uncontrolled Name Dhawan, Vikas ; Shree Guru Gobind Singh Tricentenary University, Gurugram – 122 505, India
Debnath, Kishore ; Department of Mechanical Engineering, National Institute of Technology Meghalaya, Shillong – 793 003, India
Singh, Inderdeep ; Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee – 247 667, India
Singh, Sehijpal ; Department of Mechanical Engineering, Guru Nanak Dev Engineering College, Ludhiana – 141 006, India
 
Uncontrolled Index Term Composites, Natural fillers, Drilling, Forces, Neural network
 
Summary, etc. In this paper, the drilling behavior of a new class of composite materials has been experimentally investigated. Thecomposite laminates have been manufactured using glass fibers, epoxy resin, and filler materials. The abundantly availableagro-based waste materials (coconut coir, rice husk, and wheat husk) have been used as filler materials. The drillingexperiments have been performed at several levels of feed (0.03 to 0.3 mm/rev.) and speed (90 to 2800 RPM) using differenttypes of drill bits. The effect of these parameters on the drilling forces (axial thrust and torque) has been analyzed for alltypes of laminates under investigation. The artificial neural network-based models have also been proposed to compute thedrilling forces. The fitness of the models has been measured in terms of mean percentage error between the predicted andactual values. From the investigation, it has been found that the drilling forces computed by the neural network models werequite close to the experimental values.
 
Publication, Distribution, Etc. Indian Journal of Engineering and Materials Sciences (IJEMS)
2021-01-11 15:40:19
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/IJEMS/article/view/45063
 
Data Source Entry Indian Journal of Engineering and Materials Sciences (IJEMS); ##issue.vol## 27, ##issue.no## 3 (2020): Indian Journal of Engineering and Materials Sciences
 
Language Note en
 
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